Structural and functional brain alterations in laryngeal dystonia: A coordinate‐based activation likelihood estimation meta‐analysis

Abstract Laryngeal dystonia (LD) is an isolated, task‐specific, focal dystonia characterized by intermittent spasms of laryngeal muscles impairing speech production. Although recent studies have demonstrated neural alterations in LD, the consistency of findings across studies is not well‐established, limiting their translational applicability. We conducted a systematic literature search to identify studies reporting stereotactic coordinates of peak structural and functional abnormalities in LD patients compared to healthy controls, followed by a coordinate‐based activation likelihood estimation meta‐analysis. A total of 21 functional and structural neuroimaging studies, including 31 experiments in 521 LD patients and 448 healthy controls, met the study inclusion criteria. The multimodal meta‐analysis of these studies identified abnormalities in the bilateral primary motor cortices, the left inferior parietal lobule and striatum, the right insula, and the supplementary motor area in LD patients compared to healthy controls. The meta‐analytical findings reinforce the current view of dystonia as a neural network disorder and consolidate evidence for future investigations probing these targets with new therapies.

On the other hand, despite their impact on shaping the current understanding of dystonia pathophysiology, the differences in employed neuroimaging modalities, scanning protocols, analytical paradigms, and patient selection criteria between the studies have introduced discrepancies and ambiguities to the interpretation of their findings (Ramdhani & Simonyan, 2013).This, in turn, hindered a comprehensive characterization of the LD neuroimaging signature, especially for translational applications, such as probing candidate brain targets with novel therapies.
To consolidate the findings of reported neuroimaging studies and identify a consistent and reproducible set of abnormal brain regions contributing to LD pathophysiology, we conducted a systematic activation likelihood estimation (ALE) meta-analysis of published to date functional and structural neuroimaging literature in patients with LD.The ALE methodology uses a random effects algorithm to find agreement across subject cohorts and reported activation clusters, incorporates variable uncertainty based on the cohort size, and limits the effect of a single experiment (Eickhoff et al., 2012).Thus, the ALE meta-analytical approach allowed us to model the activation clusters as a spatial probability distribution function and map the likelihood of above-chance convergence in the location of reported effects in LD patients.

| Literature search and article selection
A PubMed literature search to identify neuroimaging studies in LD patients was performed between November 14, 2022, and January 24, 2024, using Covidence systematic review software (Veritas Health Innovation, Melbourne, Australia; available at www.covidence.org) in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Page et al., 2021).
The literature search was performed using the following query: The resultant articles were independently screened by two researchers (NK and GB) first for their title and abstract to determine their relevance for this meta-analysis and then for the full text to extract data.The inclusion criteria were (1) an original, peer-reviewed article, (2) no review or case studies, and (3) reported coordinates of peak abnormality in the standard coordinate system.The inter-screener agreement rate was 0.88 (κ = 0.68) for the title and abstract selection and 0.90 (κ = 0.81) for the full-text review.The cases of disagreement between the two screeners on the title and abstract selection (11.3% of all articles) and full-text review (2.0% of all articles) were resolved with independent input from the senior investigator (KS).
The full-text review of selected articles was conducted to extract the following data: (1) the study design; (2) cohort size; (3) subject demographics (age, sex, native language, handedness, and LD clinical phenotype); (4) scanner type (manufacturer, model, and strength); (5) task/condition of interest (e.g., vowel production, speech production, reading, resting, silent fixation); ( 6 In articles reporting multiple group comparisons (e.g., different LD clinical phenotypes vs. healthy controls) or more than one imaging modality, each comparison was treated as a separate experiment in the meta-analyses.Each experiment was further categorized as a task-production fMRI/MEG/PET/EEG, resting-state fMRI, or structural MRI study based on the imaging modality used.

| ALE meta-analysis
To determine both the modality-specific overlapping cross-modality abnormalities in LD, four separate coordinate-based ALE metaanalyses were conducted as follows: (1) task-production experiments, (2) resting-state experiments, (3) structural experiments, and (4) all combined functional and structural experiments.ALE meta-analyses were performed using GingerALE software (version 3.0.2) (Eickhoff et al., 2009(Eickhoff et al., , 2012)); statistical analysis and visualization of the resultant spatial probabilistic maps were conducted using AFNI software.First, the peak coordinates in the MNI space were converted to the AFNI standard Talairach-Tournoux space using the icbm2tal transform (Lancaster et al., 2007)

| RESULTS
The PubMed search yielded a total of 195 articles, 14 of which were identified as duplicates and removed (Figure 1).Among the 181 remaining articles, 140 were excluded as irrelevant to this study after the title and abstract screening because of the wrong patient population (n = 90), wrong study design (n = 31), case report (n = 11), non-human study (n = 7), and executive summary (n = 1).
T A B L E 1 Characteristics of 21 studies included in the coordinate-based meta-analysis of abnormal brain regions in laryngeal dystonia.least 3 months after their last botulinum toxin injection and were fully symptomatic at the time of the study participation.
The third article (Putzel et al., 2018) stated an overlap in study participants because it used the regions of abnormal activity from another study (Battistella et al., 2016) to perform functional connectivity analysis and investigate the association between abnormal connectivity and polygenic risk of dystonia.We conducted an influence analysis (Viechtbauer & Cheung, 2010) to determine the impact of this article (Putzel et al., 2018) on the final results by removing its data from the meta-analysis.The influence analysis found that the identified metaanalytical regions were not derived as a result of the overlap in LD patients between these two studies.Therefore, the final meta-analysis included all 21 articles.Simonyan, 2022;Termsarasab et al., 2016), symptom-evoking syllable production (n = 3) (Simonyan & Ludlow, 2010, 2012), continuous vowel production (n = 4) (Haslinger et al., 2005;Kiyuna et al., 2014;Kothare et al., 2022), narrative speech production (n = 1) (Ali et al., 2006), reading digits (n = 1) (Kiyuna et al., 2017), and voice perception (n = 1) (Kanazawa et al., 2020) O PET with regional cerebral blood flow (rCBF) (Ali et al., 2006), and one experiment used EEG to examine spectral topography (Ehrlich et al., 2023).A total of 194 coordinates were extracted from these experiments and used in the ALE meta-analysis.

| Modality-specific ale meta-analysis of functional and structural studies
Five significant clusters were located in the right primary motor cortex (area 4p) and IPL (area PGp), the left premotor cortex (area 6) and putamen extending to GPi, and the bilateral SMA at FWE-corrected p ≤ .05(Figure 2a, Table 2).
The ALE meta-analysis of 31 coordinates derived from these studies found 5 significant clusters located in the left IPL (area PFop), premotor cortex (area 6), and putamen, the bilateral SMA, and the right parietal operculum (area OP1) at FWE-corrected p ≤ .05(Figure 2b, Table 2).

| Cross-modality ALE meta-analysis of functional and structural studies
Combining all 31 functional and structural experiments in 21 articles, a total of 278 coordinates were used to identify common functional and structural alterations across all imaging modalities in LD patients.
The ALE meta-analysis found six clusters located in the bilateral primary motor cortex (area 4p), the left inferior parietal lobule (IPL, area PFop) and putamen extending to the globus pallidus internal segment (GPi), and the right insula and supplementary motor area (SMA) at FWE-corrected p ≤ .05(Figure 2d, Table 2).

| DISCUSSION
We performed a systematic meta-analytical investigation of published to date literature reporting functional and structural neural alterations in LD patients to define the most commonly affected brain regions that likely contribute to the pathophysiology of this disorder.Our key findings point to the presence of distributed abnormalities involving not only the striatum and primary motor cortex but also associative cortical regions, such as the IPL, premotor cortex, SMA, parietal operculum, and insula.These meta-analytical findings align well with the prevailing notion of dystonia as a neural network disorder (Lungu et al., 2020;Simonyan et al., 2021) and consolidate evidence for future investigations probing these targets as biomarkers for LD differential diagnostics and new therapies.
The role of both the primary motor cortex and basal ganglia has been well-established in dystonia pathophysiology and is now supported by our meta-analytical findings.Identified bilateral abnormalities in the primary motor cortex correspond to the location of the laryngeal motor cortex (LMC) (Bouchard et al., 2013;Simonyan, 2014;Simonyan & Horwitz, 2011).The LMC is an essential hub of motor execution within the speech production network, with wide-ranging connections to other cortical and subcortical regions that are hierarchically involved in sensory processing and feedback, sensorimotor integration, and motor planning during speaking (Fuertinger et al., 2015;Simonyan & Fuertinger, 2015;Valeriani & Simonyan, 2021).Through direct connections to brainstem laryngeal motoneurons, the LMC regulates the final cortical motor output during speech production (Simonyan & Horwitz, 2011).Its abnormal activity likely directly impacts the dystonic pattern of laryngeal muscle activation observed during speech production in LD patients.
As a prominent subcortical structure in both the speech production network and dystonia pathophysiology, the striatum plays a critical role in the initiation of intended actions and the suppression of Statistically significant clusters identified using coordinate-based ALE meta-analysis of (a) task-production functional activity (yellow), (b) resting-state functional connectivity (purple), (c) voxel-based morphometry and cortical thickness (blue), and (d) all functional and structural neuroimaging studies ( green) in patients with laryngeal dystonia compared to healthy controls.Gpi, globus pallidus internus; IPL, inferior parietal lobule; Ins, insula; M1, primary motor cortex; PreM, premotor cortex; Put, putamen; SMA, supplementary motor area; STG, superior temporal gyrus.
unwanted, competing motor patterns.An imbalance between the facilitatory and inhibitory effects of the direct and indirect basal ganglia pathways may manifest as an overall decrease of inhibition throughout the basal ganglia-thalamo-cortical circuitry (Hallett, 2011;Simonyan et al., 2017) and subsequently contribute to altered motor cortical execution in dystonia patients.In the current meta-analysis, functional and structural abnormalities were consistently found within the somatotopic representation of the larynx in the striatum (Simonyan & Jurgens, 2003) across all examined modalities, hence, reinforcing the notion that specific changes in this region remain a prevalent pathophysiological feature of dystonia.
However, despite their apparent involvement in dystonia pathophysiology, the previous attempts to alleviate dystonic symptoms using invasive or non-invasive neuromodulation of the basal ganglia and motor cortex have yielded highly heterogeneous results.For example, while deep brain stimulation (DBS) of basal ganglia targets has been effective in treating a variety of movement disorders, including generalized, segmental, and cervical dystonia (Jacksch et al., 2022;Lee et al., 2019;Yin et al., 2022), its benefits in LD patients remain variable, ranging from no changes to worsening of symptoms (Isaias et al., 2009).Efforts to apply non-invasive brain stimulation over the primary motor cortex in patients with focal dystonia have similarly resulted in variable outcomes, largely dependent on patient cohorts, stimulation parameters, and targeted coordinates (Morrison-Ham et al., 2022).The inconsistent speech outcomes of stimulation targeting the motor cortex and basal ganglia suggest that these regions, although integral to LD pathophysiology, may not be of a primary importance for therapeutic interventions in these patients.Conversely, the associative regions identified through this meta-analysis might represent alternative targets for neuromodulation.
To that end, our meta-analyses highlighted abnormalities in premotor, parietal, and insular regions in LD patients, all of which have been demonstrated to have strong functional and structural connections with the LMC (Kumar et al., 2016;Simonyan et al., 2009) and associated with extrinsic risk factors for this disorder (de Lima Xavier & Simonyan, 2019).The involvement of an array of these cortical regions in the dystonic network of LD is also consistent with the task-specificity of the disorder, characterized by disruptions of learned, finely skilled movements (Ramdhani et al., 2014).
Specifically, premotor regions are highly involved in motor preparation of voluntary vocal commands, with voice-related neural activity in the SMA found to precede activity in the motor cortex (Galgano & Froud, 2008).The SMA has also been attributed to higher-level functions related to speech production, including initiation and timing control, inhibitory control, complex sequencing, and task switching, and represents a key component in cortical networks as well as in the basal ganglia-thalamo-cortical loop (Hertrich et al., 2016) these abnormalities likely contribute significantly to the manifestation of LD symptomatology.
The current meta-analytical findings also strengthen evidence for the substantial role of IPL alterations in LD pathophysiology.The IPL consists of the supramarginal and angular gyri, the former of which is thought to be important in sensorimotor integration (Guenther, 2016).
Functional activation of the IPL has been shown during experimental conditions to evoke a mismatch between sensory expectations and feedback, including delayed auditory feedback, unexpected somatosensory feedback perturbations, and transitions in visual, auditory, and tactile stimuli, implying that this region is essential for sensory feedback control during the production of speech motor tasks (Downar et al., 2000;Golfinopoulos et al., 2011;Hashimoto & Sakai, 2003).Abnormal activation and functional connectivity of the IPL have been previously implicated in various forms of task-specific focal dystonia, including LD, musician's dystonia, and writer's cramp (Battistella & Simonyan, 2019;Bianchi et al., 2019;Delnooz et al., 2012;Gallea et al., 2016;Maguire et al., 2020;Putzel et al., 2018), suggesting that processing of somatosensory feedback during the production of highly skilled tasks may be perturbed in these patients.This notion is supported by a phenomenology of geste antagoniste or sensory tricks in LD patients, in which perturbations to peripheral sensory inputs, including touching the throat or humming before speaking, are able to temporarily alleviate LD symptoms (Blitzer et al., 2018).In a recent study of effective connectivity, the IPL has been found to exhibit abnormal top-down influences on the premotor cortex and putamen, supporting the hypothesis that altered parietal-premotor and parietal-putaminal information transfer may precede motor cortical changes within the dystonic network (Battistella & Simonyan, 2019).
Through a combination of lesion and neuroimaging studies, the insula has been demonstrated to play an important yet diverse and ambiguous role in speech motor control (Baldo et al., 2011;Bohland & Guenther, 2006;Dronkers, 1996).Multiple insular subdivisions have been shown to exhibit non-overlapping structural connections to cortical regions involved in articulatory modulation and motor preparation, auditory and phonological processes, and motor execution (Battistella et al., 2018).A reorganization of these subdivisions, specifically those highly connected to motor regions, and a loss of the insular hub as part of structural and functional connectome have been previously reported in LD patients (Battistella et al., 2017;Hanekamp & Simonyan, 2020).Our findings suggest that altered insular-cortical connectivity in LD likely contributes to disrupted information flow between motor planning and sensorimotor regions, potentially playing a larger than initially assumed role in LD clinical symptomatology (Hanekamp & Simonyan, 2020).
While the current meta-analysis consolidated the reported neuroimaging findings in LD, its limitations should be acknowledged.The meta-analytical cohort was comprised of LD patients with different clinical subtypes of the disorder.Among these, the majority (90.5%) of articles included adductor LD, nearly half (47.6%) of articles included abductor LD and about a quarter (23.8%) of articles included LD with dystonic tremor.The demographics of the meta-analytical study cohort follow the typical demographics of this disorder (Blitzer et al., 2018), which suggests that the reported results may be applicable to the general patient population.However, given the substantially smaller proportions of LD patients with abductor and tremor subtypes, only 1 study reporting comparisons between adductor/abductor LD and healthy controls, and none examining LD with or without dystonic tremor vs. healthy controls, separate meta-analyses of LD cohorts stratified by these clinical phenotypes were not feasible.
In conclusion, using ALE meta-analysis, we identified a robust set of functionally and structurally abnormal brain regions in LD that spatially converge across neuroimaging modalities, scanner types, and methodological paradigms.Our findings confirm the presence of extensive network-wide disruptions underlying this disorder.In addition to the basal ganglia and primary motor cortical alterations, other cortical areas, including premotor, parietal, and insular regions, are likely to represent the major pathophysiological nodes of the LD neural network.The next series of studies is warranted to discern the directionality of abnormal influences within this pathophysiological network, as well as the relationships between functional and structural changes, which would help clarify the pathophysiological mechanisms that trigger the development of LD.Future studies may also probe the identified meta-analytical brain region as biomarkers for differential diagnosis of LD from other neurological disorders or nonneurological conditions mimicking dystonic voice.Furthermore, these regions might represent new targets for novel therapeutic interventions using centrally acting medications or neuromodulation for restoration of neural network function.
and inputted into the ALE algorithm.Each coordinate was modeled as a Gaussian spatial probability distribution function with a full-width half maximum (FWHM) derived from the number of subjects in each meta-analysis, accounting for the spatial uncertainty of individual coordinates.Modeled activation (MA) maps were calculated by finding the union across the Gaussian functions for all coordinates in each experiment.The ALE scores were quantified as the union of MA maps across all experiments and transformed into Z-scores.Statistical significance of the resultant Z-scores was set at a family-wise error (FWE)-corrected p ≤ .05 with voxelwise p ≤ .001and a minimum cluster size of 240 mm 3 .
Probabilistic clusters of functional and structural brain abnormalities in LD patients.